Principal ML Engineer

Prodege, LLC; United States; On-site; USD 270,000 - 330,000; Full time

Benefits offered by this job

Benefits package including medical, +

Flexible PTO

Eight paid holidays

Job summary

Prodege is seeking a Principal Machine Learning Engineer who will own the ML stack end-to-end, from problem framing to deployment, monitoring, and lifecycle optimization. You will build production ML systems that affect revenue, margin, and user value at scale.

You’ll lead and mentor a team in a fast-moving AdTech/MarTech environment, partnering with data engineers and product teams to deliver measurable business impact.

Qualifications

• Extensive experience building and operating production ML systems end to end.
• Strong background in ranking, personalization, and experimentation in ML systems.
• Proven ability to deliver ML solutions that impact revenue, margins, and user value.
• Hands-on expertise across problem framing, feature strategy, deployment, monitoring, and retraining.

Responsibilities

• Lead design, build, and evolve production ML algorithms and systems.
• Drive critical implementations and prove approaches in production.
• Architect scalable ML systems for offline training and online inference.

Skills

8+ years software engineering

5+ years production ML systems

MLOps

Machine learning engineering

Leadership & mentoring

Job description

Read this part first:
This is a role for someone who wants to own more than models. We're looking for a

Job Description

This is a role for someone who wants to own more than models. We're looking for a Principal Machine Learning Engineer to shape the future of machine learning across Prodege's Performance Marketing business, and this is a deeply hands‑on principal role: you lead by building, shipping, and operating production ML systems, not by staying at the architecture or strategy layer. If you want to hand designs to a team and review from a distance, this isn't your role, and that's okay. But if you're the kind of engineer who owns the ML stack end to end—from problem framing and feature strategy through model development, experimentation, deployment, observability, and lifecycle optimization—and wants your work to move revenue, margin, user value, and marketplace efficiency in a fast-moving AdTech / MarTech environment, keep reading. You'll build production ML systems for a business serving 120M+ registered users that has delivered $2B+ in lifetime rewards, powered by a data platform with 50M events per day, 500M records of daily pipeline throughput, a 100TB Iceberg lake, and 50 Kafka topics and growing across batch and real-time workflows. If you enjoy building real-world ML systems, working close to the business, and helping a team move toward a more AI‑first engineering model, this role is for you.

Prodege

A cutting‑edge marketing and consumer insights platform, Prodege has charted a course of innovation in the evolving technology landscape by helping leading brands, marketers, and agencies uncover the answers to their business questions, acquire new customers, increase revenue, and drive brand loyalty & product adoption. Bolstered by a major investment by Blackstone in Q1 2026, Prodege looks forward to more growth and innovation to empower our partners to gather meaningful, rich insights and better market to their target audiences. As an organization, we go the extra mile to "Create Rewarding Moments" every day for our partners, consumers, and team. Come join us today!

What You'll Own

• The architecture and delivery of offline / online ML systems, feature pipelines, inference patterns, feedback loops, and monitoring
• End-to-end ML systems spanning feature generation, training, inference, experimentation, monitoring, and lifecycle management
• Production ML algorithms and decisioning systems across ranking, rewards, ROAS / LTV, personalization, and offer optimization
• Experimentation frameworks that connect model performance to business outcomes
• Production‑grade standards across MLOps, observability, retraining, governance, and reliability
• Hands‑on technical leadership for the ML team through direct contribution, code reviews, and mentoring
• The evolution of ML toward a more AI‑first way of working

What Makes This Role Exciting

• You’ll directly shape how machine learning drives revenue, margin, and user value
• You’ll work on analytically complex problems across ranking, rewards, ROAS, LTV, personalization, and optimization in a high‑scale AdTech / MarTech environment
• You’ll own ML from system design through production outcome, not just model development
• You’ll build on top of a real production data platform operating at scale: 50M daily events, 500M daily pipeline records, a 100TB Iceberg lake, and 50 Kafka topics and growing
• You’ll inherit a strong experimentation culture with 30+ ML experiments per month, 10 live experiments already this year, and a feature‑rich data foundation with 1,000+ features, including user and item embeddings
• You’ll build on real business momentum — our best ranking models are already outperforming the prior models
• You’ll have principal‑level scope to influence both the systems being built and how the broader ML organization works
• You’ll help push the organization toward a more AI‑first engineering future

What You’ll Do

• Lead the design, build, and evolution of production ML algorithms and systems that drive real business outcomes
• Personally drive critical implementations, proving out new approaches in production before scaling them across the team
• Architect and ship scalable ML systems across offline training, online inference, feature pipelines, feedback loops, and model monitoring
• Build and evolve solutions across ranking and recommendation, rewards optimization, ROAS / LTV prediction, campaign and offer optimization, and experimentation and decisioning systems
• Establish robust experimentation and measurement frameworks, including offline evaluation, A/B testing, KPI design, and post‑launch validation
• Make key decisions on MLOps, tooling, infrastructure, serving patterns, observability, and platform architecture
• Partner closely with Data Engineering, BI, Product, Engineering, and business teams to create reliable data foundations and connect ML work to business priorities
• Drive an AI‑first mindset by using AI to accelerate research, prototyping, feature engineering, experiment analysis, debugging, documentation, and developer productivity
• Mentor ML engineers and data scientists by leading through direct contribution and raising the bar on model quality, technical judgment, and engineering rigor

What You’ll Bring (the Must-haves)

• 8+ years of experience in software engineering, machine learning engineering, MLOps, or related technical fields
• 5+ years building, deploying, and supporting production ML systems at scale
• Strong experience in AdTech, MarTech, Growth, Performance Marketing, or adjacent domains
• Strong hands‑on background in ranking, recommendation, rewards / incentives, ROAS / LTV prediction, and personalization / optimization systems
• Proven experience designing, shipping, and operating production ML systems end to end
• Strong understanding of offline / online ML architecture, feature engineering and feature platforms, model serving patterns, experimentation frameworks for ML systems, A/B testing and measurement design, and MLOps, retraining, monitoring, and governance
• Experience partnering closely with Data Engineering / BI / Analytics teams to create clean, scalable, and trustworthy data foundations for ML
• Strong system design skills with sound judgment across performance, reliability, scalability, and cost
• Ability to guide teams toward an AI‑first way of working, while maintaining strong validation and engineering discipline
• Strong technical leadership and mentoring capability, with the ability to influence across teams without direct authority
• Comfort operating in ambiguity and still driving systems into production

Bonus Points (the Nice‑to‑haves)

• Experience with counterfactual reasoning, causal inference, or uplift modeling
• Experience in rewards, offer ecosystems, customer value optimization, or monetization platforms
• Experience with streaming or near‑real‑time decisioning systems
• Experience building ML platforms or shared experimentation infrastructure
• Master's degree or PhD in AI, Machine Learning, or a quantitative field
• Familiarity with modern AI‑assistant / AI‑first development practices across engineering and data science teams

Pay Transparency

The anticipated base salary range for this position is $300,000 to $375,000. The final salary offered to a successful candidate will be dependent on several factors that may include, but are not limited to; the type and length of experience within the job, type and length of experience within the industry, the type and length of knowledge and skills for the position, education, training, etc. Prodege is a multi‑state employer and final compensation within this range could be impacted by work location. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits

Prodege Benefits

Prodege offers a comprehensive benefits package to US Full‑time employees including medical, dental, vision, STD, LTD and basic life insurance. Employees receive flexible PTO, as well as paid sick leave prorated based on hire date. US Employees have eight paid holidays throughout the calendar year.

Equal Employment Opportunity Statement

At Prodege, we are committed to creating a diverse and inclusive environment. We are proud to be an Equal Opportunity Employer and do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other characteristic protected by law. We encourage individuals of all backgrounds to apply.

FCIHO

Employers will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of FCIHO.